Index-based evaluation of vegetation response to meteorological drought in Northern China

作者:Li, R (Li, Rui)[ 1 ] ; Wang, JA (Wang, Jing'ai)[ 2 ] ; Zhao, TJ (Zhao, Tianjie)[ 1 ] ; Shi, JC (Shi, Jiancheng)[ 1 ]

NATURAL HAZARDS

卷: 84  期: 3  页: 2179-2193

DOI: 10.1007/s11069-016-2542-3

出版年: DEC 2016

摘要

The short-term relationship between drought and vegetation growth is important for drought monitoring. This paper integrated precipitation-based Effective Drought Index (EDI) and SPOT-VEGETATION 1-km Normalized Difference Vegetation Index (NDVI) at 10-day scale to quantify spatial pattern of short-term vegetation response to drought in Northern China. Coefficient of determination (R (2)) was used to identify drought influence and temporal relationship. The paper analyzed correlations between EDI and Normalized Difference Vegetation Index Anomaly (NDVIA) within 30-km radius domain at 178 stations in Northern China from 1998 to 2013. In order to validate the correlation results, we compared them with conventional growth period (May-September) scale precipitation-NDVI relationship and 0.25-degree VUA-NASA soil moisture product at 10-day basis from 2003 to 2009. We further explored EDI-NDVI correlations at 1-km vegetation pixels of 8 typical sites. The results show that (1) R (2) between 10-day EDI and average NDVIA at 30-km radius domain is significant in regions with 200-400 mm mean annual precipitation; NDVIA has a mainly 10-day time lag behind EDI; (2) R (2) at 10-day scale relationship fit Gaussian curve better than those at growth period scale; there are similar spatial patterns of both precipitation-NDVI and EDI-NDVI correlations; (3) The correlations between 0.25A degrees remote sensing soil moisture and NDVI from 2003 to 2009 show the same 10-day time lag and a similar spatial pattern as EDI-NDVI method; (4) 1-km grassland pixels have significant R (2) and 10-day time lag in drier regions. This paper suggests EDI-NDVI correlation method is useful to identify more details of drought-vegetation relationship. The above results are expected to provide some guidance e.g., 10-day time lag in drought management in semi-arid zones.

通讯作者地址: Li, R (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China